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PyBindingCurve, simulation and curve fitting to complex binding systems at equilibrium

View ORCID ProfileSteven Shave, Yan-Kai Chen, View ORCID ProfileNhan T. Pham, View ORCID ProfileManfred Auer
doi: https://doi.org/10.1101/2020.11.06.371344
Steven Shave
1University of Edinburgh, School of Biological Sciences, University of Edinburgh, The King’s Buildings, Max Born Crescent, CH Waddington Building, Edinburgh, Scotland EH9 3BF, United Kingdom
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  • ORCID record for Steven Shave
  • For correspondence: s.shave@ed.ac.uk manfred.auer@ed.ac.uk
Yan-Kai Chen
1University of Edinburgh, School of Biological Sciences, University of Edinburgh, The King’s Buildings, Max Born Crescent, CH Waddington Building, Edinburgh, Scotland EH9 3BF, United Kingdom
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Nhan T. Pham
1University of Edinburgh, School of Biological Sciences, University of Edinburgh, The King’s Buildings, Max Born Crescent, CH Waddington Building, Edinburgh, Scotland EH9 3BF, United Kingdom
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Manfred Auer
1University of Edinburgh, School of Biological Sciences, University of Edinburgh, The King’s Buildings, Max Born Crescent, CH Waddington Building, Edinburgh, Scotland EH9 3BF, United Kingdom
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  • For correspondence: s.shave@ed.ac.uk manfred.auer@ed.ac.uk
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Abstract

Understanding multicomponent binding interactions in protein-ligand, protein-protein and competition systems is essential for fundamental biology and drug discovery. Hand deriving equations quickly becomes unfeasible when the number of components is increased, and direct analytical solutions only exist to a certain complexity. To address this problem and allow easy access to simulation, plotting and parameter fitting to complex systems at equilibrium, we present the Python package PyBindingCurve. We apply this software to explore homodimer and heterodimer formation culminating in the discovery that under certain conditions, homodimers are easier to break with an inhibitor than heterodimers and may also be more readily depleted. This is a potentially valuable and overlooked phenomenon of great importance to drug discovery. PyBindingCurve may be expanded to operate on any equilibrium binding system and allows definition of custom systems using a simple syntax. PyBindingCurve is available under the MIT license at: https://github.com/stevenshave/pybindingcurve as Python source code accompanied by examples and as an easily installable package within the Python Package Index.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/stevenshave/pybindingcurve

  • https://stevenshave.github.io/pybindingcurve

  • https://pypi.org/project/pybindingcurve

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 08, 2020.
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PyBindingCurve, simulation and curve fitting to complex binding systems at equilibrium
Steven Shave, Yan-Kai Chen, Nhan T. Pham, Manfred Auer
bioRxiv 2020.11.06.371344; doi: https://doi.org/10.1101/2020.11.06.371344
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PyBindingCurve, simulation and curve fitting to complex binding systems at equilibrium
Steven Shave, Yan-Kai Chen, Nhan T. Pham, Manfred Auer
bioRxiv 2020.11.06.371344; doi: https://doi.org/10.1101/2020.11.06.371344

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